Free
Explore GPUFlight and run occasional labs.
- 1 GB monthly ingestion
- 7-day retention
- Trace profiling
GPU profiling and observability
Profile CUDA and ROCm workloads, inspect kernels and timelines, and monitor every GPU from one browser dashboard.
Open-source clientNo credit card

Start with the workflow you need today. The same dashboard connects the results.
Profile
Trace timings, occupancy, SASS, PC sampling, and memory behavior without losing the context of the full run.
Explore profilingMonitor
Follow utilization, memory, power, and temperature across hosts, then connect a system change to the workload behind it.
Explore monitoringBuild and learn
Use Workbench for your own code or learn performance concepts through guided labs on real NVIDIA GPUs.
Open the playgroundFollow the cause
Start with the full run, open the kernel that stands out, and keep the evidence together instead of switching between disconnected captures.

Use GPUFlight with an existing CUDA application, including PyTorch workloads.
gpufl trace --upload -- python train.pyStart with one command. Add deeper profiling passes only when you need them.
GPUFlight uploads the run and organizes kernels, timelines, memory activity, and metrics in your browser.
Find the bottleneck, share the session, or compare the result with another run or host.
Need SDK instrumentation or deployment options? Read the docs.
Start free, add deeper practice tools, or scale profiling to more GPUs and people.
Free
Explore GPUFlight and run occasional labs.
Practice
Build hands-on CUDA performance skills.
Individual
Profile and optimize your own workloads.
Team
Share GPU performance work with a small team.
Enterprise
Scale GPUFlight to your environment.
Need a custom plan? Talk to us.
Start with a free profile or explore the live demo.